Triple
T31310436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balto |
E798447
|
entity |
| Predicate | distanceCoveredInFinalLeg |
P81748
|
FINISHED |
| Object | approximately 55 miles |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: approximately 55 miles | Statement: [Balto, distanceCoveredInFinalLeg, approximately 55 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceCoveredInFinalLeg Context triple: [Balto, distanceCoveredInFinalLeg, approximately 55 miles]
-
A.
distancePerLeg
chosen
Indicates the distance covered in a single leg or segment of a multi-part journey or route.
-
B.
distanceTraveled
Indicates the total length of the path an entity has moved over a period of time or between two points.
-
C.
lastKnownLeg
Indicates the most recent or final leg (segment) in a sequence of legs associated with an entity or journey.
-
D.
laterFlightDistance
Indicates the distance associated with a flight that occurs later in time relative to another referenced flight.
-
E.
distanceOfCourse
Indicates the length or total distance covered by a course or route.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01bb9c33cc8190a95ba124d97edf99 |
completed | May 11, 2026, 11:21 a.m. |
| PD | Predicate disambiguation | batch_6a01bb6772148190a243d1141ad0a237 |
completed | May 11, 2026, 11:20 a.m. |
Created at: April 29, 2026, 9:15 p.m.